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Deep convolutional networks have achieved successful performance in data mining field. However, training large networks still remains a challenge, as the training data may be insufficient and the model can easily get overfitted. Hence the training process is usually combined with a model regularization. Typical regularizers include weight decay, Dropout, etc. In this paper, we propose a novel regularizer,...
Confronted with severe environment issues, large scale utilization and development of wind energy and solar energy that are regenerative, non-pollution, green and clean, the best way for power generation and grid synchronization of distributed energy is to develop intelligence micro-grid. Amongst micro-grid, batteries will be connected with super capacitors to form hybrid energy storage system. Batteries...
The human visual system proves smart in extracting both global and local features. Can we design a similar way for unsupervised feature learning? In this paper, we propose anovel pooling method within an unsupervised feature learningframework, named Rich and Robust Feature Pooling (R2FP), to better explore rich and robust representation from sparsefeature maps of the input data. Both local and global...
This paper presents an electronic documents anonymous appraisal protocol using the unconditional anonymous of proxy ring signature and differentiating of the original signature and the proxy signature. The security analysis of the protocol shows that it has a good anonymity and capability of coalition-resistance. This protocol can reduce the possibility which the declarer pulls strings for someone...
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